Jun Shi, Zhifeng Zhang, Rui Gao, Zhi Chen
In response to the dual challenge of global agricultural greening and digital transformation, it is imperative for agricultural colleges and universities in China to restructure talent cultivation models to support the development of sustainable and intelligent agriculture. This study combines literature analysis, case studies, and questionnaire surveys to identify misalignments between the current agricultural education system and industry needs. Focusing on educational objectives, curricula, practical training, and faculty expertise, the authors propose a novel four-dimensional collaborative cultivation model, “Objectives–Curriculum–Practice–Faculty”. This model centers on interdisciplinary course clusters (e.g., agricultural artificial intelligence and blockchain traceability), industry–academia-integrated training platforms (e.g., smart agriculture innovation centers), and a Dynamic Adjustment Mechanism (DCAM). To support the implementation of this model, this study advances policy recommendations from three perspectives. First, governments should accelerate reforms by providing special funding support and formulating legislation on industry–academia integration. Second, universities must establish early-warning response mechanisms. Third, enterprises must participate in developing education on ecosystems. This paper establishes both a theoretical framework and a practical pathway to transform agricultural education, offering significant referential value for global agricultural institutions adapting to technological revolutions.